Real-time stream processing is becoming a critical component in any cloud architecture. The processing times can be measured in microseconds instead of hours or days. However, what if your application requires combining data in motion with data at rest in the cloud? How can you speed up your real-time stream processing?
The talk will focus on speeding real-time stream processing by using concurrency and caching mechanisms in the cloud, it will show why real-time stream processing alone is not enough, and how it can be used in a combination of data at rest to offer more capabilities, and eventually make real-time applications go faster and smarter. The talk will include a demo using the Hazelcast open-source platform and will be available on Github.
The talk will focus on speeding real-time stream processing by using concurrency and caching mechanisms in the cloud, it will show why real-time stream processing alone is not enough, and how it can be used in a combination of data at rest to offer more capabilities, and eventually make real-time applications go faster and smarter. The talk will include a demo using the Hazelcast open-source platform and will be available on Github.
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